CN115879327B - Digital twinning-based damage efficiency evaluation method, device, equipment and medium - Google Patents
Digital twinning-based damage efficiency evaluation method, device, equipment and medium Download PDFInfo
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Abstract
The application discloses a digital twinning-based damage effectiveness evaluation method, device, equipment and medium, which relate to the field of virtual training and weapon effectiveness verification and comprise the following steps: constructing damage efficiency data of the weapon to be evaluated by utilizing a digital twin technology, and creating a data driving model under multi-source heterogeneous based on the damage efficiency data so as to obtain a virtual weapon model corresponding to the weapon to be evaluated; determining a weight value of the virtual weapon model at a preset moment according to the time slice sequence and an evaluation rule in the damage evaluation criterion database; the method comprises the steps of superposing weight values and condition data into damage efficiency data of a virtual weapon model based on superposition rules to obtain a target virtual weapon model; and calculating the damage efficiency data of the target virtual weapon model in a preset time period to obtain the damage efficiency data of each time slice of the target virtual weapon model. The method and the device utilize the digital twin technology and the time slicing technology to perform data processing and damage efficiency evaluation, and can obtain accurate damage efficiency evaluation results.
Description
Technical Field
The present invention relates to the field of virtual training and weapon effectiveness verification, and in particular, to a digital twin-based damage effectiveness evaluation method, apparatus, device and storage medium.
Background
The weapon damage efficiency evaluation in the current virtual simulation field is mostly judged by setting an injury value in advance, so that the problems of stiff injury judgment, unrealistic damage effect and the like exist, the real-time evaluation of the weapon damage efficiency at a certain moment cannot be performed, the result damage effect can only be judged, and the problems of single interpretation dimension, narrow variability, fuzzy quantification, inaccurate damage efficiency evaluation and the like exist due to the lack of calculation and procedural calculation evaluation in multidimensional space and time.
Disclosure of Invention
Accordingly, the present invention is directed to a digital twin-based method, apparatus, device and medium for evaluating the damage performance of weapon equipment, which is suitable for dynamic evaluation of the damage performance of weapon equipment, and can meet the requirements of rule parameter editing deduction evaluation in time slicing state and weapon performance damage effect evaluation in multi-time space dimension. The specific scheme is as follows:
in a first aspect, the present application discloses a digital twinning-based damage effectiveness assessment method comprising:
Constructing damage efficiency data of a weapon to be evaluated by utilizing a digital twin technology, and creating a data driving model under multi-source heterogeneous based on the damage efficiency data of the weapon to be evaluated so as to obtain a virtual weapon model corresponding to the weapon to be evaluated;
determining a weight value of the virtual weapon model at a preset moment according to the time slice sequence and an evaluation rule in a pre-constructed damage evaluation criterion database;
the weight value and the preset condition data are overlapped to the damage efficiency data of the virtual weapon model in a preset time period based on a preset overlapping rule, so that a target virtual weapon model is obtained;
and calculating the damage efficiency data of the target virtual weapon model in the preset time period to obtain the damage efficiency data of each time slice of the target virtual weapon model.
Optionally, the determining the weight value of the virtual weapon model at the preset moment according to the time slice sequence and the evaluation rule in the pre-constructed damage evaluation criterion database includes:
pairing the damage efficiency data with the virtual weapon model according to the time slice sequence to obtain a paired virtual weapon model, and determining a weight value of the paired virtual weapon model at a preset time based on an evaluation rule in the damage evaluation criterion database.
Optionally, the stacking the weight value and the preset condition data into the damage efficiency data of the virtual weapon model in the preset time period based on a preset stacking rule to obtain a target virtual weapon model includes:
establishing a mapping relation between the time slice and the evaluation rule, and superposing the weight value to the damage efficiency data of the virtual weapon model in the preset time period according to the mapping relation to obtain a corrected virtual weapon model;
performing data superposition on the corrected virtual weapon model based on preset condition data to obtain the target virtual weapon model; the condition data comprise preset simulation physical environment, temperature and humidity, wind power and meteorological data.
Optionally, the calculating the damage efficiency data of the target virtual weapon model in the preset time period to obtain the damage efficiency data of each time slice of the target virtual weapon model includes:
calculating the damage efficiency of the target virtual weapon model based on an ammunition damage model, collision detection analysis and damage level analysis model to obtain a damage result of the target virtual weapon model;
Confirming the damage result based on a judging rule to obtain a target confirmation result, and calculating the damage efficiency data of the target virtual weapon model in the preset time period based on data corresponding to the target confirmation result to obtain damage efficiency data of each time slice of the target virtual weapon model; the target validation result is characterized in that the target virtual weapon model hits a target object.
Optionally, the validating the damage result based on the evaluation rule to obtain a target validation result includes:
confirming the damage result according to the data of ammunition hit on the target object to obtain a target confirmation result; the data includes hit angle, hit location and ammunition damage data to the target object.
Optionally, the calculating the damage efficiency data of the target virtual weapon model in the preset time period based on the data corresponding to the target confirmation result to obtain the damage efficiency data of each time slice of the target virtual weapon model includes:
respectively determining characteristic parameters before and after the target object is hit based on data corresponding to the target confirmation result, determining action data of a damage element on the target object based on the characteristic parameters, and calculating damage probability of the target object by using the action data;
And calculating the damage efficiency data of all the target virtual weapon models in the preset time period based on the damage probability of the target object, and determining the damage efficiency data of each time slice of the target virtual weapon model based on the damage efficiency data of all the target virtual weapon models.
Optionally, after calculating the damage efficiency data of the target virtual weapon model in the preset time period to obtain the damage efficiency data of each time slice of the target virtual weapon model, the method further includes:
calculating the damage efficiency data of the target virtual weapon model for a plurality of times to obtain a damage efficiency database, and determining the comprehensive damage efficiency data of each time slice of the target virtual weapon model within the preset time period based on the saturated gunfire coverage striking factors and the damage efficiency database so as to realize the comprehensive evaluation of the damage capacity of the weapon to be evaluated.
In a second aspect, the present application discloses a digital twinning-based lesion efficacy assessment device comprising:
the model acquisition module is used for constructing damage efficiency data of the weapon to be evaluated by utilizing a digital twin technology, and creating a data driving model under multi-source heterogeneous based on the damage efficiency data of the weapon to be evaluated so as to obtain a virtual weapon model corresponding to the weapon to be evaluated;
The weight value determining module is used for determining the weight value of the virtual weapon model at the preset moment according to the time slice sequence and an evaluation rule in a pre-constructed damage evaluation criterion database;
the model determining module is used for adding the weight value and preset condition data into the damage efficiency data of the virtual weapon model in a preset time period based on a preset adding rule so as to obtain a target virtual weapon model;
the data determining module is used for calculating the damage efficiency data of the target virtual weapon model in the preset time period to obtain the damage efficiency data of each time slice of the target virtual weapon model.
In a third aspect, the present application discloses an electronic device comprising:
a memory for storing a computer program;
and a processor for executing the computer program to implement the steps of the digital twin-based damage effectiveness evaluation method.
In a fourth aspect, the present application discloses a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the aforementioned digital twinning-based lesion performance assessment method.
When virtual damage efficiency evaluation is carried out, firstly, digital twin technology is utilized to construct damage efficiency data of a weapon to be evaluated, and a data driving model under multi-source heterogeneous is created based on the damage efficiency data of the weapon to be evaluated so as to obtain a virtual weapon model corresponding to the weapon to be evaluated; determining a weight value of the virtual weapon model at a preset moment according to the time slice sequence and an evaluation rule in a pre-constructed damage evaluation criterion database; the weight value and the preset condition data are overlapped to the damage efficiency data of the virtual weapon model in a preset time period based on a preset overlapping rule, so that a target virtual weapon model is obtained; and calculating the damage efficiency data of the target virtual weapon model in the preset time period to obtain the damage efficiency data of each time slice of the target virtual weapon model. Therefore, the method and the device can realize quantitative statistics of the damage efficiency index of the weapon striking link by carrying out time slicing splitting on the weapon firing striking process based on the real data of weapon damage, comprehensively evaluate the damage efficiency coefficient at the preset time through analyzing the dimension of the time slice, realize comprehensive striking damage efficiency evaluation of the weapon, and have important significance for realizing modeling of a parameterized weapon and analysis of weapon fight efficiency under the time course. Meanwhile, compared with the traditional weapon efficiency evaluation strategy, the method disclosed by the invention considers the influence of the external environment on the damage efficiency of the weapon equipment, and combines the multidimensional information such as the striking angle, the striking position and the like, thereby disclosing a more practical damage efficiency evaluation method.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a digital twinning-based damage effectiveness evaluation method disclosed in the present application;
FIG. 2 is a flow chart of a collision detection analysis disclosed herein;
FIG. 3 is a flowchart illustrating the basic steps of a collision detection analysis disclosed herein;
FIG. 4 is a basic flow diagram of a collision subject preliminary screening disclosed herein;
FIG. 5 is a schematic view of a collision zone division of the present disclosure;
FIG. 6 is a schematic view of a collision detection coordinate system definition disclosed herein;
FIG. 7 is a flowchart of a specific digital twin-based damage effectiveness assessment method disclosed herein;
FIG. 8 is a schematic diagram of a digital twin-based damage performance evaluation device according to the present disclosure;
fig. 9 is a block diagram of an electronic device disclosed in the present application.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The weapon damage efficiency evaluation in the current virtual simulation field is mostly judged by setting an injury value in advance, so that the problems of stiff injury judgment, unrealistic damage effect and the like exist, the real-time evaluation of the weapon damage efficiency at a certain moment cannot be performed, the result damage effect can only be judged, and the problems of single interpretation dimension, narrow variability, fuzzy quantification, inaccurate damage efficiency evaluation and the like exist due to the lack of calculation and procedural calculation evaluation in multidimensional space and time. Aiming at the invention, the invention aims to provide a dynamic evaluation method suitable for the damage efficiency of the weapon equipment, which meets the requirements of rule parameter editing deduction evaluation under the time slice state and weapon efficiency damage effect evaluation under the multi-time-space dimension.
Referring to fig. 1, an embodiment of the invention discloses a digital twinning-based damage effectiveness evaluation method, which comprises the following steps:
step S11, constructing damage efficiency data of the weapon to be evaluated by utilizing a digital twin technology, and creating a data driving model under multi-source heterogeneous based on the damage efficiency data of the weapon to be evaluated so as to obtain a virtual weapon model corresponding to the weapon to be evaluated.
In the embodiment, the digital twin technology is to create a virtual model of a physical entity in a high-fidelity simulation modeling mode, build a super data driving model by means of multi-source heterogeneous data integration, and perform simulation analysis and optimization on entity behaviors, so that high-confidence simulation prediction is obtained. It can be seen that the digital twin technology is utilized to construct the damage efficiency data of the weapon to be evaluated, and the damage efficiency data is input to construct the data driving model under the multi-source heterogeneous condition. The obtained data driving model under the heterogeneous multisource is identical with weapon entity data and structure, and the virtual weapon model corresponding to the weapon to be evaluated is obtained. So that the destruction efficiency data of the physical weapon at the moment T+n can be disassembled according to the time axis in the appointed time period.
And step S12, determining a weight value of the virtual weapon model at a preset moment according to the time slice sequence and an evaluation rule in a pre-constructed damage evaluation criterion database.
In this embodiment, the time slicing technique is a technique for displaying a data section at a certain time T in a data volume of a virtual simulation deduction result, so as to implement real-time deduction of performance data slicing of the damaged performance at time t+n. And the quantitative data is provided for evaluating the reliability weak links of the damage evaluation through time slice division of standard operation links of weapon damage striking. To obtain the weight value of the virtual weapon model at the preset time, the damage efficiency data and the virtual weapon model are paired according to the time slice sequence to obtain a paired virtual weapon model, and the weight value v of the paired virtual weapon model at the preset time is determined based on the evaluation rule in the damage evaluation criterion database, and the weight value v is calculated as follows.
Wherein P is the weapon damage probability, a is the weapon firing rate, b is the weapon initial rate, R is caliber, M is weapon weight, and q is aiming correction coefficient.
Firstly, constructing a basic damage evaluation criterion database, matching associated weapon entities (weapons) for judging damage effectiveness according to a time slice sequence, performing arrangement analysis on the weapon damage effectiveness according to a time axis, intercepting an initial moment as time T, and generating a weight value of the weapon at the current moment according to an evaluation criterion in the damage evaluation criterion database. It should be noted that the evaluation criteria for different weapons are different, and that selecting the corresponding evaluation criteria can more accurately yield the results.
And S13, based on a preset superposition rule, superposing the weight value and preset condition data into the damage efficiency data of the virtual weapon model in a preset time period to obtain a target virtual weapon model.
In this embodiment, the weight value and the preset condition data are superimposed into the damage efficiency data of the virtual weapon model in a preset time period based on a preset superimposition rule, and a mapping relationship between a time slice and the evaluation rule is first required to be established, and the weight value is superimposed into the damage efficiency data of the virtual weapon model in the preset time period according to the mapping relationship, so as to obtain a corrected virtual weapon model; then, based on preset condition data, carrying out data superposition on the corrected virtual weapon model to obtain the target virtual weapon model; the condition data comprise preset simulation physical environment, temperature and humidity, wind power and meteorological data. And the data superposition is carried out on the weapon entity object, namely the virtual weapon model, according to the set data of the simulated physical environment, the temperature and humidity, the wind power, the weather and the like. It can be understood that the set simulation physical environment, temperature and humidity, wind power, weather and other data are overlapped, so that the influence of the external environment on the damage efficiency of the weapon equipment is considered.
Step S14, calculating the damage efficiency data of the target virtual weapon model in the preset time period to obtain damage efficiency data of each time slice of the target virtual weapon model.
In this embodiment, calculating the damage efficiency data of the target virtual weapon model in the preset time period to obtain the damage efficiency data of each time slice of the target virtual weapon model includes: calculating the damage efficiency of the virtual weapon model based on an ammunition damage model, collision detection analysis and damage grade analysis model to obtain a damage result of the target virtual weapon model; when performing collision detection analysis, as shown in fig. 2, first, entity object association of collision detection analysis is performed based on a simulation task sequence; then, based on the associated object state data, data preparation of collision detection analysis is performed; then, performing collision parameter calculation based on a collision detection algorithm; based on the collision detection judgment rule, making collision condition judgment, including collision part and area range; finally, the collision detection analysis result is displayed and output in a two-dimensional graph and table form. For the basic steps of collision detection analysis, as shown in FIG. 3, step 1: through gridding the battlefield space, the probability of collision of the entity object is primarily filtered by using grids, which is beneficial to improving the collision detection efficiency. Namely, the collision objects are primarily screened, as shown in fig. 4, wherein the grid should be capable of covering the collision detection objects, and the side length of the grid can be calculated based on the killing radius and the killing object size, and the calculation formula is as follows:
Wherein R is the killing radius, L is the length of the damaged object, and a is the adjusting coefficient, preferably 5.
Step 2: and further performing intersection judgment on the filtered collision objects, removing the reversely maneuvering entity objects, and then performing sampling compensation on the high-speed target by using a DR algorithm to calculate the collision position and angle. That is, collision intersection judgment is performed, and the plane is divided into 8 areas in 360 degrees, and the collision area range is defined, as shown in fig. 5. If collision detection analysis is performed on the collision main body a and the collision object B, if the collision portion is in the yellow region in the drawing, collision is considered to occur, otherwise no collision is considered to occur. When collision occurs, judging the range of the area according to the angle of the position of the collision part. Based on the distance azimuth relationship of the weapon's incident distance azimuth and the distance azimuth of the device assembly, it is determined at which distance azimuth the device assembly at that azimuth is affected. The x/y/z axes of the defined earth system are east, north and sky, respectively, and the x/y/z axes of the physical system are front, right and bottom, respectively, as shown in fig. 6. Defining the attitude angle of the body axis system on the ground axis system as follows: yaw angle (right offset positive), pitch angle (head up positive), roll angle (right roll positive). The original coordinate system of the weapon position is the geodetic coordinate system 
However, the coordinates of each device component are defined under the body axis, and it is assumed that the coordinates of a certain device component are +.>
It is therefore necessary to convert weapon position under the body axis to enter unified calculation. The method of transforming the geodetic system into the geodetic system follows a general geospatial coordinate transformation formula and is not described in detail herein. Let the ground axis coordinate of weapon be +.>
The formula of the transformation matrix for transforming the earth system into the body system is as follows: />
Thus, the azimuth angle (the angle with the x-axis) and the elevation angle (the angle with the XY-plane) under the body axis are respectively:
let the polar coordinates of the weapon in the body axis system be
If the angular coordinate of the device in the body axis is, determining whether the weapon envelope is intersected with the device component or not can be determined by determining the distance envelope and the angular relation, and the determination formula is that
Wherein: dR represents the distance threshold at which the two intersect;
an azimuth threshold representing the intersection of the two; />
Indicating the high and low angular threshold at which the two intersect. For a high-speed application entity, assuming that the actual motion position is P1, the motion position obtained by simulation by using a DR algorithm is +.>
DR provides several classical algorithms: 1. position 1 = position 0, i.e. remain unchanged; 2. position 1=position 0+velocity× (T1-T0), corresponding to making uniform motion; 3. position 1 = position 0+ velocity x (T1-T0) +1/2 x acceleration x (T1-T0) square. Optionally selecting One of the algorithms performs a position compensation calculation.
Step 3: and analyzing the result of the collision calculation to obtain the collision position, the influence range and related equipment. The collision result analysis is carried out, and based on the collision intersection analysis result, the collision range, associated equipment and influence condition are analyzed for the object entity which is collided, so that data input is provided for damage evaluation. Wherein, the record specification of the collision detection analysis results is shown in table 1.
TABLE 1
Then confirming the damage result based on a judging rule to obtain a target confirmation result, and calculating the damage efficiency data of the target virtual weapon model in the preset time period based on data corresponding to the target confirmation result to obtain damage efficiency data of each time slice of the target virtual weapon model; the target validation result is characterized in that the target virtual weapon model hits a target object. The method comprises the steps of performing injury correction on a hit target through an ammunition injury model, setting the protection capability of the hit target, performing multidimensional calculation, and introducing a collision detection analysis and damage level analysis model to perform calculation. The damage efficiency of the virtual weapon model is calculated from multiple aspects to obtain the damage result of each time slice of the target virtual weapon model, so that the real data of the physical damage is used for carrying out time slice splitting on the weapon transmitting and striking process, the damage efficiency index quantification statistics of the weapon striking link of the weapon entity can be realized, the damage efficiency coefficient under the T moment is comprehensively evaluated through the analysis of the dimension of the time slice, the comprehensive striking damage efficiency evaluation of the weapon entity is realized, and the method has important significance for realizing the modeling of the parameterized weapon entity and the analysis of the weapon fight efficiency under the time process. In this embodiment, after calculating the damage efficiency data of the target virtual weapon model in the preset time period to obtain the damage efficiency data of each time slice of the target virtual weapon model, the method further includes: calculating the damage efficiency data of the target virtual weapon model for a plurality of times to obtain a damage efficiency database, and determining the comprehensive damage efficiency data of each time slice of the target virtual weapon model within the preset time period based on the saturated gunfire coverage striking factors and the damage efficiency database so as to realize comprehensive evaluation of the damage capacity of the weapon to be evaluated. The comprehensive damage capability of the weapon is evaluated by calculating the striking efficiency of the weapon for multiple times and simultaneously introducing the saturated gunfire to cover the striking factors for calculation to obtain the damage result of each time slice in the time of T+n under multiple factors. Therefore, the method considers the gunfire coverage striking condition, evaluates the damage value of the coverage area aiming at the saturated gunfire striking condition, and further meets the requirement of actual combat simulation.
As can be seen from the above, when performing virtual damage efficiency evaluation, the present application firstly uses digital twin technology to construct damage efficiency data of a weapon to be evaluated, and creates a data driving model under heterogeneous multiple sources based on the damage efficiency data of the weapon to be evaluated, so as to obtain a virtual weapon model corresponding to the weapon to be evaluated; determining a weight value of the virtual weapon model at a preset moment according to the time slice sequence and an evaluation rule in a pre-constructed damage evaluation criterion database; the weight value and the preset condition data are overlapped to the damage efficiency data of the virtual weapon model in a preset time period based on a preset overlapping rule, so that a target virtual weapon model is obtained; and calculating the damage efficiency data of the target virtual weapon model in the preset time period to obtain the damage efficiency data of each time slice of the target virtual weapon model. Therefore, the method and the device can realize quantitative statistics of the damage efficiency index of the weapon striking link by carrying out time slicing splitting on the weapon firing striking process based on the real data of weapon damage, comprehensively evaluate the damage efficiency coefficient at the preset time through analyzing the dimension of the time slice, realize comprehensive striking damage efficiency evaluation of the weapon, and have important significance for realizing modeling of a parameterized weapon and analysis of weapon fight efficiency under the time course. Meanwhile, compared with the traditional weapon efficiency evaluation strategy, the method disclosed by the invention considers the influence of the external environment on the damage efficiency of the weapon equipment, and combines the multidimensional information such as the striking angle, the striking position and the like, thereby disclosing a more practical damage efficiency evaluation method.
Based on the above embodiments, the present application may propose a dynamic evaluation method suitable for the damage effectiveness of weapon equipment based on digital twin technology and time slicing technology. Next, a detailed description will be made with respect to a process of acquiring the destruction efficacy data of each time slice of the target virtual weapon model. Referring to fig. 7, an embodiment of the present invention discloses a specific digital twin-based damage effectiveness evaluation method, which includes:
step S21, calculating the damage efficiency of the target virtual weapon model based on the ammunition damage model, the collision detection analysis and the damage level analysis model so as to obtain a damage result of the target virtual weapon model.
In this embodiment, after the target virtual weapon model is obtained, the damage efficiency of the target virtual weapon model is calculated based on the ammunition damage model, the collision detection analysis and the damage level analysis model, so as to obtain the damage result of the target virtual weapon model, thereby meeting the requirement of weapon efficiency damage effect evaluation under the multi-time space dimension.
Step S22, confirming the damage result based on a judging rule to obtain a target confirmation result, respectively determining characteristic parameters before and after the target object is hit based on data corresponding to the target confirmation result, determining action data of the damage element on the target object based on the characteristic parameters, and calculating damage probability of the target object by using the action data; the target validation result is characterized in that the target virtual weapon model hits a target object.
In this embodiment, the validating the damage result based on the evaluation rule to obtain the target validation result includes: confirming the damage result according to the data of ammunition hit on the target object to obtain a target confirmation result; the data includes hit angle, hit location and ammunition damage data to the target object. Namely, the damage accuracy, timeliness and effectiveness index are confirmed according to the hit angle, hit position and data such as the penetration damage or damage condition of the ammunition received by the target when the ammunition hits the target. Therefore, the method combines multidimensional information such as the striking angle, the striking position and the like, constructs a more practical damage efficiency evaluation method, and meets the requirements of weapon efficiency damage effect evaluation under multiple time-space dimensions.
Step S23, calculating the damage efficiency data of all the target virtual weapon models in the preset time period based on the damage probability of the target object, and determining the damage efficiency data of each time slice of the target virtual weapon model based on the damage efficiency data of all the target virtual weapon models.
In this embodiment, the characteristic parameters before and after striking are compared and judged, and the target damage probability is calculated according to the obtained action condition of the damage element on the target.
Wherein, the liquid crystal display device comprises a liquid crystal display device,
for the destructive efficacy data of a single time slice, +.>
For the ith t+n time slice, N is the total number of time slices. And counting the damage efficiency data of the weapon entity in all T+n time, thereby obtaining the killing energy efficiency of each slice in the T+n time in the whole weapon striking process. It should be noted that if the standard target is a point target, the point killer weapon is selected to strike, and the core pseudo code of the damage calculation is as follows:
if (Point target)
{
for (i= 1;i < = ammunition number m; i++// have m ammunition attack targets)
{
if (Rand () < = weapon destruction index D hit probability P visibility level K)// calculation formula of point target
The target is destroyed;
else
the target is not destroyed;
}
}
the sub-target performance decay level is a map of the sub-target physical damage level as a function of physical damage. Assuming that the physical damage degree of the sub-target is P (x), the initial performance value of the target is P0 (x), and the performance value after the sub-target is subjected to the corresponding damage is P (x), the relationship between the target performance attenuation degree and the target damage degree is:
wherein: p (x) is the efficacy decay function; p (x) is more than or equal to 0 and less than or equal to P0 (x) is more than or equal to 1; p (x) is the physical extent of damage of the sub-target; the specific expression of the function f needs to be determined according to different situations. Different mission tasks and battlefield environments of the targets cause the expression of the function f to be different. Since the corresponding degree of performance decay at certain physical corrupted nodes is known, lagrange (lagrangian) linear interpolation is typically used to determine the expression type of function f.
Compared with the traditional weapon efficiency evaluation strategy, the method disclosed by the invention considers the influence of the external environment on the damage efficiency of the weapon equipment, and combines the multidimensional information such as the striking angle, the striking position and the like to construct a more practical damage efficiency evaluation method, thereby meeting the requirement of weapon efficiency damage effect evaluation under the multi-time-space dimension.
Referring to fig. 3, an embodiment of the present invention discloses a digital twin-based damage effectiveness evaluation device, which includes:
the model acquisition module 11 is configured to construct damage efficiency data of a weapon to be evaluated by using a digital twin technology, and create a data driving model under heterogeneous multiple sources based on the damage efficiency data of the weapon to be evaluated, so as to obtain a virtual weapon model corresponding to the weapon to be evaluated;
the weight value determining module 12 is configured to determine a weight value of the virtual weapon model at a preset time according to the time slice sequence and an evaluation rule in a pre-constructed damage evaluation criterion database;
the model determining module 13 is configured to superimpose the weight value and preset condition data on the basis of a preset superimposing rule onto the damage efficiency data of the virtual weapon model in a preset period of time, so as to obtain a target virtual weapon model;
The data determining module 14 is configured to calculate the damage efficiency data of the target virtual weapon model in the preset time period, so as to obtain damage efficiency data of each time slice of the target virtual weapon model.
When virtual damage efficiency evaluation is carried out, firstly, digital twin technology is utilized to construct damage efficiency data of a weapon to be evaluated, and a data driving model under multi-source heterogeneous is created based on the damage efficiency data of the weapon to be evaluated so as to obtain a virtual weapon model corresponding to the weapon to be evaluated; determining a weight value of the virtual weapon model at a preset moment according to the time slice sequence and an evaluation rule in a pre-constructed damage evaluation criterion database; the weight value and the preset condition data are overlapped to the damage efficiency data of the virtual weapon model in a preset time period based on a preset overlapping rule, so that a target virtual weapon model is obtained; and calculating the damage efficiency data of the target virtual weapon model in the preset time period to obtain the damage efficiency data of each time slice of the target virtual weapon model. Therefore, the method and the device can realize quantitative statistics of the damage efficiency index of the weapon striking link by carrying out time slicing splitting on the weapon firing striking process based on the real data of weapon damage, comprehensively evaluate the damage efficiency coefficient at the preset time through analyzing the dimension of the time slice, realize comprehensive striking damage efficiency evaluation of the weapon, and have important significance for realizing modeling of a parameterized weapon and analysis of weapon fight efficiency under the time course. Meanwhile, compared with the traditional weapon efficiency evaluation strategy, the method disclosed by the invention considers the influence of the external environment on the damage efficiency of the weapon equipment, and combines the multidimensional information such as the striking angle, the striking position and the like, thereby disclosing a more practical damage efficiency evaluation method.
In some specific embodiments, the weight value determining module 12 includes:
the weight value determining unit is used for pairing the damage efficiency data with the virtual weapon model according to the time slice sequence to obtain a paired virtual weapon model, and determining the weight value of the paired virtual weapon model at a preset moment based on the evaluation rule in the damage evaluation criterion database.
In some specific embodiments, the model determination module 13 includes:
the corrected virtual weapon model obtaining unit is used for establishing a mapping relation between the time slice and the evaluation rule, and superposing the weight value to the damage efficiency data of the virtual weapon model in the preset time period according to the mapping relation so as to obtain the corrected virtual weapon model;
the target virtual weapon model acquisition unit is used for carrying out data superposition on the corrected virtual weapon model based on preset condition data so as to obtain the target virtual weapon model; the condition data comprise preset simulation physical environment, temperature and humidity, wind power and meteorological data.
In some specific embodiments, the data determination module 14 includes:
The damage result acquisition unit is used for calculating the damage efficiency of the target virtual weapon model based on an ammunition damage model, collision detection analysis and damage grade analysis model so as to obtain the damage result of the target virtual weapon model;
the damage efficiency data acquisition unit is used for confirming the damage result based on a judgment rule to obtain a target confirmation result, and calculating the damage efficiency data of the target virtual weapon model in the preset time period based on data corresponding to the target confirmation result to obtain damage efficiency data of each time slice of the target virtual weapon model; the target validation result is characterized in that the target virtual weapon model hits a target object.
In some specific embodiments, the data determination module 14 includes:
the target confirmation result acquisition unit is used for confirming the damage result according to the data when the ammunition hits the target object so as to obtain a target confirmation result; the data includes hit angle, hit location and ammunition damage data to the target object.
In some specific embodiments, the data determination module 14 includes:
The damage probability calculation unit is used for respectively determining characteristic parameters before and after the target object is hit based on data corresponding to the target confirmation result, determining action data of the damage element on the target object based on the characteristic parameters, and calculating the damage probability of the target object by using the action data;
the data determining unit is used for calculating the damage efficiency data of all the target virtual weapon models in the preset time period based on the damage probability of the target object, and determining the damage efficiency data of each time slice of the target virtual weapon model based on the damage efficiency data of all the target virtual weapon models.
In some specific embodiments, the data determination module 14 further comprises:
the comprehensive evaluation unit is used for calculating the damage efficiency data of the target virtual weapon model for a plurality of times to obtain a damage efficiency database, and determining the comprehensive damage efficiency data of each time slice of the target virtual weapon model in the preset time period based on the saturated gunfire coverage striking factors and the damage efficiency database so as to realize comprehensive evaluation of the damage capacity of the weapon to be evaluated.
Further, the embodiment of the present application further discloses an electronic device, and fig. 4 is a block diagram of an electronic device 20 according to an exemplary embodiment, where the content of the figure is not to be considered as any limitation on the scope of use of the present application.
Fig. 4 is a schematic structural diagram of an electronic device 20 according to an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input output interface 25, and a communication bus 26. Wherein the memory 22 is used for storing a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the digital twin-based damage effectiveness assessment method disclosed in any of the foregoing embodiments. In addition, the electronic device 20 in the present embodiment may be specifically an electronic computer.
In this embodiment, the power supply 23 is configured to provide an operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and an external device, and the communication protocol to be followed is any communication protocol applicable to the technical solution of the present application, which is not specifically limited herein; the input/output interface 25 is used for acquiring external input data or outputting external output data, and the specific interface type thereof may be selected according to the specific application requirement, which is not limited herein.
The memory 22 may be a carrier for storing resources, such as a read-only memory, a random access memory, a magnetic disk, or an optical disk, and the resources stored thereon may include an operating system 221, a computer program 222, and the like, and the storage may be temporary storage or permanent storage.
The operating system 221 is used for managing and controlling various hardware devices on the electronic device 20 and computer programs 222, which may be Windows Server, netware, unix, linux, etc. The computer program 222 may further comprise a computer program capable of performing other specific tasks in addition to the computer program capable of performing the digital twin based method of assessing the efficacy of damage performed by the electronic device 20 as disclosed in any of the previous embodiments.
Further, the application also discloses a computer readable storage medium for storing a computer program; the computer program, when executed by the processor, implements the disclosed digital twin-based damage effectiveness evaluation method. For specific steps of the method, reference may be made to the corresponding contents disclosed in the foregoing embodiments, and no further description is given here.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, so that the same or similar parts between the embodiments are referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing has outlined the detailed description of the preferred embodiment of the present application, and the detailed description of the principles and embodiments of the present application has been provided herein by way of example only to facilitate the understanding of the method and core concepts of the present application; meanwhile, as those skilled in the art will have modifications in the specific embodiments and application scope in accordance with the ideas of the present application, the present description should not be construed as limiting the present application in view of the above.
Claims (9)
1. A digital twinning-based damage effectiveness assessment method, comprising:
constructing damage efficiency data of a weapon to be evaluated by utilizing a digital twin technology, and creating a data driving model under multi-source heterogeneous based on the damage efficiency data of the weapon to be evaluated so as to obtain a virtual weapon model corresponding to the weapon to be evaluated;
determining a weight value of the virtual weapon model at a preset moment according to the time slice sequence and an evaluation rule in a pre-constructed damage evaluation criterion database;
the weight value and the preset condition data are overlapped to the damage efficiency data of the virtual weapon model in a preset time period based on a preset overlapping rule, so that a target virtual weapon model is obtained;
Calculating the damage efficiency data of the target virtual weapon model in the preset time period to obtain the damage efficiency data of each time slice of the target virtual weapon model;
wherein the calculating the damage efficiency data of the target virtual weapon model in the preset time period to obtain the damage efficiency data of each time slice of the target virtual weapon model includes:
calculating the damage efficiency of the target virtual weapon model based on an ammunition damage model, collision detection analysis and damage level analysis model to obtain a damage result of the target virtual weapon model;
confirming the damage result based on a judging rule to obtain a target confirmation result, and calculating the damage efficiency data of the target virtual weapon model in the preset time period based on data corresponding to the target confirmation result to obtain damage efficiency data of each time slice of the target virtual weapon model; the target validation result is characterized in that the target virtual weapon model hits a target object.
2. The method for evaluating the efficacy of damage based on digital twinning according to claim 1, wherein the determining the weight value of the virtual weapon model at the preset time according to the time slice sequence and the evaluation rule in the pre-constructed damage evaluation criterion database comprises:
Pairing the damage efficiency data with the virtual weapon model according to the time slice sequence to obtain a paired virtual weapon model, and determining a weight value of the paired virtual weapon model at a preset time based on an evaluation rule in the damage evaluation criterion database.
3. The method of claim 1, wherein the superimposing the weight value and the preset condition data into the damage performance data of the virtual weapon model in the preset time period based on a preset superimposing rule to obtain a target virtual weapon model comprises:
establishing a mapping relation between the time slice and the evaluation rule, and superposing the weight value to the damage efficiency data of the virtual weapon model in the preset time period according to the mapping relation to obtain a corrected virtual weapon model;
performing data superposition on the corrected virtual weapon model based on preset condition data to obtain the target virtual weapon model; the condition data comprise preset simulation physical environment, temperature and humidity, wind power and meteorological data.
4. The digital twin based lesion efficacy assessment method according to claim 1, wherein validating the lesion result based on the evaluation rule to obtain a target validation result comprises:
Confirming the damage result according to the data of ammunition hit on the target object to obtain a target confirmation result; the data includes hit angle, hit location and ammunition damage data to the target object.
5. The method of claim 1, wherein calculating the damage performance data of the target virtual weapon model within the predetermined time period based on the data corresponding to the target validation result to obtain the damage performance data of each time slice of the target virtual weapon model comprises:
respectively determining characteristic parameters before and after the target object is hit based on data corresponding to the target confirmation result, determining action data of a damage element on the target object based on the characteristic parameters, and calculating damage probability of the target object by using the action data;
and calculating the damage efficiency data of all the target virtual weapon models in the preset time period based on the damage probability of the target object, and determining the damage efficiency data of each time slice of the target virtual weapon model based on the damage efficiency data of all the target virtual weapon models.
6. The digital twinning-based destruction performance assessment method according to claim 4 or 5, wherein after calculating the destruction performance data of the target virtual weapon model over the predetermined period of time to obtain the destruction performance data of each time slice of the target virtual weapon model, further comprising:
calculating the damage efficiency data of the target virtual weapon model for a plurality of times to obtain a damage efficiency database, and determining the comprehensive damage efficiency data of each time slice of the target virtual weapon model within the preset time period based on the saturated gunfire coverage striking factors and the damage efficiency database so as to realize the comprehensive evaluation of the damage capacity of the weapon to be evaluated.
7. A digital twinning-based lesion efficacy assessment device comprising:
the model acquisition module is used for constructing damage efficiency data of the weapon to be evaluated by utilizing a digital twin technology, and creating a data driving model under multi-source heterogeneous based on the damage efficiency data of the weapon to be evaluated so as to obtain a virtual weapon model corresponding to the weapon to be evaluated;
the weight value determining module is used for determining the weight value of the virtual weapon model at the preset moment according to the time slice sequence and an evaluation rule in a pre-constructed damage evaluation criterion database;
The model determining module is used for adding the weight value and preset condition data into the damage efficiency data of the virtual weapon model in a preset time period based on a preset adding rule so as to obtain a target virtual weapon model;
the data determining module is used for calculating the damage efficiency data of the target virtual weapon model in the preset time period to obtain the damage efficiency data of each time slice of the target virtual weapon model;
the data determining module is specifically configured to calculate the damage efficiency of the target virtual weapon model based on an ammunition damage model, collision detection analysis and damage level analysis model, so as to obtain a damage result of the target virtual weapon model; confirming the damage result based on a judging rule to obtain a target confirmation result, and calculating the damage efficiency data of the target virtual weapon model in the preset time period based on data corresponding to the target confirmation result to obtain damage efficiency data of each time slice of the target virtual weapon model; the target validation result is characterized in that the target virtual weapon model hits a target object.
8. An electronic device, comprising:
a memory for storing a computer program;
a processor for executing the computer program for implementing a digital twin based lesion efficacy assessment method according to any of claims 1 to 6.
9. A computer readable storage medium for storing a computer program which, when executed by a processor, implements a digital twin based lesion efficacy assessment method according to any of claims 1 to 6.
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